Neo4j has this great IDE-a: How about we stuff all our graph workspace, database, algorithms and visualisation wizardry in one place?
Neo4j for Graph Data Science offers a ready-to-hand library of algorithms that the vendor said were optimised to run over tens of billions of nodes and relationships. It includes production features, such as deterministic seeding which provides starter values and consistent results for reproducible machine learning workflows. It also contains its own in-memory graph database for training and test data.
Read more: https://www.theregister.co.uk/2020/04/09/neo4j_analytics_environment/
Keywords: alicia frame • Amy Hodler • GDS • graph data science